Only six years old, CS has already inspired more than a thousand papers and pulled in millions of dollars in federal grants. In 2006, Candès’ work on the topic was rewarded with the $500,000 Waterman Prize, the highest honor bestowed by the National Science Foundation.

Compressed sensing isn’t useful just for solving today’s technological problems; the technique will help us in the future as we struggle with how to treat the vast amounts of information we have in storage. The world produces untold petabytes of data every day — data that we’d like to see packed away securely, efficiently, and retrievably. At present, most of our audiovisual info is stored in sophisticated compression formats. But in the CS future, Candès believes, we’ll record just 20 percent of the pixels in certain images, like expensive-to-capture infrared shots of astronomical phenomena. Because we’re recording so much less data to begin with, there will be no need to compress. And instead of steadily improving compression algorithms, we’ll have steadily improving decompression algorithms that reconstruct the original image more and more faithfully from the stored data.

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